Hybrid Methods in Feature Selection: A Data Classification Perspective: Hybrid Feature Selection Methods are the proven methods for Large Scale Feature Selection - Tapa blanda

Subramanian, Senthamarai Kannan

 
9783844399240: Hybrid Methods in Feature Selection: A Data Classification Perspective: Hybrid Feature Selection Methods are the proven methods for Large Scale Feature Selection
Tapa blanda
ISBN 10: 3844399240 ISBN 13: 9783844399240
Editorial: LAP LAMBERT Academic Publishing, 2011

Sinopsis

In recent years, data have become increasingly larger in both number of instances and number of features in many applications. This enormity may cause serious problems to many machine learning algorithms with respect to scalability and learning performance. Therefore, feature selection is essential for the machine learning algorithms while handling high dimensional datasets. Many traditional search methods have shown promising results in a number of feature selection problems. However, as the number of features increases extremely, most of these existing methods face the problem of intractable computational time. Since no single feature selection method could handle all requirements of feature selection in real world datasets, hybrid methods prsented here are the tested methods for effecive Feature Selection.One viable option is to apply a ranking feature selection method to obtain a manageable number of top ranked features which could be further handled by traditional feature selection methods for further analysis.

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Reseña del editor

In recent years, data have become increasingly larger in both number of instances and number of features in many applications. This enormity may cause serious problems to many machine learning algorithms with respect to scalability and learning performance. Therefore, feature selection is essential for the machine learning algorithms while handling high dimensional datasets. Many traditional search methods have shown promising results in a number of feature selection problems. However, as the number of features increases extremely, most of these existing methods face the problem of intractable computational time. Since no single feature selection method could handle all requirements of feature selection in real world datasets, hybrid methods prsented here are the tested methods for effecive Feature Selection.One viable option is to apply a ranking feature selection method to obtain a manageable number of top ranked features which could be further handled by traditional feature selection methods for further analysis.

Biografía del autor

Dr S.SENTHAMARAI KANNAN is presently working as Assistant Professor with Thiagarajar College of Engineering , India. He has published nine papers in reputed international journals including Elsevier Knowledge Based Systems and the CODATA Data Science Journal and he has been cited by many as the authority in the field of Feature Selection.

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Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2011
Idioma
Inglés
ISBN 10 
3844399240
ISBN 13 
9783844399240
Encuadernación
Tapa blanda
Número de páginas
64
Contacto del fabricante
no disponible
Persona responsable
no disponible